Sunday, September 27, 2009

Another one in a series of risk management write-ups. (I guess this is becoming more and more common as this is my full-time job right now.) I came across a recent article in the Washington Post about the malpractices in lending practiced by subprime affiliates of large banks and the reluctance of the Federal Reserve to play an effective regulatory role. The article is here.

The article talks about how the Fed gradually withdrew in its regulatory responsibility on consumer finance companies as these were not "banks". The Fed reduced its oversight of these companies because it believed it did not have the right jurisdiction to regulate these companies. This was despite a considerable amount of evidence from individuals and other watch-dog bodies that were reporting egregious practices by these institutions. Another big factor that was playing at the time was the good old "markets self-regulate" belief (I was going to say theory and I corrected myself. Maybe I should say, myth.) but I am not going to spend too much time in this post on that.

Why did the Fed turn its head away from the problem? One of my hypotheses is too much of a reliance on "literalism". The Fed chose to literally interpret its mandate of regulating banks and decided to look no further - even though there were other institutions whose practices were exactly the same as what any bank would do. Literalism is a particular problem I have observed in the US. It is the strong objection to interpret a piece of policy/ law developed years ago in line with the world today. This problem is most commonly seen with respect to the US Constitution and its various amendments. But "literalism" is a problem when it creates blind spots in end-to-end risk management and ends up threatening the viability of the corporation or, as in this case, the entire financial system. An effective risk manager is expected to be proactive in identifying gaps in the end-to-end risk management and being open to taking on more responsibility, proposing changes to the system, as needed.

The other problem was that the Fed tended to be influenced more by grand economic theories and conceptual/ philosophical frameworks and decided to discount the data coming up from the ground. According to the article, the Fed tended to discount these pieces of anecdotal evidence as their place within a broader framework or their systematic impact was well-known. This is another problem often with smart people. It is a thinking that goes: I think and talk in concepts, abstractions and theories. Therefore, I will only listen when other people talk the same way. Now this is a problem which afflicts many of us, and therefore might be even borderline acceptable in everyday life. But this is fatal in risk management, where your job is to anticipate different ways in which the system can be at risk. An effective risk manager is expected to constantly keep her radar up for pieces of information that might be contrary to a pre-existing framework and have an efficient means of investigating whether the anecdotal evidence points to any material threat.

Finally, one important lesson that is worth taking way is that when it comes to human created systems, there is no one overarching framework or "truth". Because interactions between humans and institutions created by humans are not governed by the laws of physics, there are often no absolutes in these things. Many theories or frameworks could be simultaneously true or may apply in portions of the world we are trying to understand. Depending on the prevailing conditions, one set of rules may hold. And as conditions change or as the previous framework pushes the environment to one extreme, the competing framework often becomes more relevant and appropriate to apply. It is often practical to keep one's mind open to other theories and frameworks. Ideological alignment or obsession with one "truth" system only makes one closed to other explanations or possibilities.

Wednesday, September 16, 2009

The credit crisis of 2008, or the Great Recession as it is now famous as, has had many many books written on it. Writers from across the ideological spectrum have written about why the crisis occured and how their brand of ideology could have prevented the crisis. Which is why I was skeptical when I came across this piece which seemed to rehash the story of the collapse of Lehman. I was pleasantly surprised that this article was about one element that has been whispered off and on, but not very convincingly: about risk management based on common sense. (The reader needs to get past the title and the opening blurb, though. The title seems to suggest the credit crisis would have never taken place if Goldman Sachs hadn't spotted the game early enough. That is plain ridiculous. The leveraging of the economy + the decline in lending standards created a ticking time-bomb. But I digress.)

The article is not about having some fancy risk management metrics or why our models are wrong or why we should not trust a Ph.D that offers to build a model for you. (Of course, all of these elements contributed to why the crisis was ignored for all these years.) Instead, the article recounts a real-life meeting that took place in Goldman Sachs at the end of 2006. The meeting was convened by Goldman CFO, David Viniar, based on some seemingly innocuous happenings. The company had been losing money on its mortgage backed securities for 10 days in a row. The resulting deep-dive into the details of the trades pointed to a sense of unease about the mortgage market. Which then caused Goldman to famously back-off from the market.

I'll leave the reading to you to get more details of what happened. But some thoughts on what contribute to effective risk management practices.

- A real-life feel for the business. You can't be just into the models, you need to be savvy enough to understand how the models you build interact with the real world outside. And it is an appreciation of this interaction that cause the hairs to stand at the back of your neck when you encounter something that just doesn't seem right.- Proper role of risk management in the decision making hierarchy. Effective risk management takes place when the risk governance has the authority to put the brakes on risk takers (i.e., the traders, in this case). In Goldman, there were a number of enablers for this type of interaction to take place effectively. Most importantly, risk management reported to the CFO, i.e. high enough in the corporate heirarchy. Second, investment decisions needed a go-ahead from both the risk takers and risk governance.- Mutual respect between risk governance and risk takers. Goldman encourages a collaborative style of decision making. This allows multiple conflicting opinions to be present at the table. Minority opinions are encouraged and appreciated. Over time, this fosters a culture that genuinely tolerates dissonance of opinions. This also allows the CFO to be influenced by the comptroller group as much as he typically would by the trading group.- Finally, a certain intellectual probity to acknowledge what it does not know or understand. During the meeting, the Goldman team was not able to pinpoint what their source of unease was. But they were able to honestly admit that they didn't really understand what was going on, but that it was also most appropriate to bring the ship to harbour, given their blindspot about what they didn't know. It takes courage to back-off from an investing decision, saying "I don't understand this well enough" in the alpha-male investment banking culture.

Thursday, September 10, 2009

I have talked about the economy in a couple of previous posts. This was here talking about green shoots, and about the signs of frailness in the recovery. Over the months of April through August, the life of this blog, news about the economy did seem mixed. The first clear signs that things were beginning to stabilize came around the May timeframe when the drumbeat of negative economic news first started to turn mixed. The jobless claims did not rise as quickly as anticipated, the economy continued to lose jobs but fell off from the rate of close to 0.5 million a month. Around the same time period, existing home sales started to pick up for the first time in more than 2 years and finally in August, the sales pickup translated to rise in prices, for the first time in nearly 2 and a half years.

Meanwhile, Asia continued to power ahead, creating hope and optimism that it would serve as the engine for the stabilization and subsequent growth of the US economy. But even as sectors such as auto, manufacturing and - in some geographies - retail sales have started to show modest increases, job growth still eludes the economy. Quoting the WSJ blog Real Time Economics, a rough sketch of the numbers looks something like this. Average hours worked is declining at an annual rate of nearly 3%, based on quarterly numbers from earlier this year. This is largely driven by the job cuts, but also by anaemic hiring on part of companies. On the other hand, economic indicators point to the GDP growth returning to its cruising rate of about 2-3% a year. The combination of reduced work hours and economic growth translates to a positive growth for this interesting metric called Labor Productivity. One can therefore expect a productivity jump of nearly 4-6% in the third quarter. And given that incomes are flat, this is going to be good news for corporate profits. Dow at 11,000 by the end of year, anyone?

It has been said earlier that this looks like the famous jobless recovery that everyone fears. My take on what is going on. The slumping economy has given corporations the leeway to embrace job automation and computer-driven efficiency measures in a pretty radical manner. The people getting eased out are the ones who have enjoyed a successful run at holding down 'Old Economy' jobs in a world which doesn't value these jobs any longer. When the housing bubble was on, the inefficiency of these jobs never surfaced. But as corporate bottomlines are exposed, companies are making do with fewer and more talented people. Employees who are adept at computers and the use of technology and in its power to ruthlessly driven efficiencies.

For every one of us, this is a sign of how ephemeral our much 'valued' skills are in today's economic reality. A call to action that will be heard by the smart amongst us, but which will also be sadly ignored by many.

Tuesday, September 1, 2009

I am going to now talk about the second kind of job, that is going to become increasingly attractive for knowledge workers. In the first type of job, I talked about the advances in computing and communication capabilities and technology that make it extremely attractive for jobs that had been performed hitherto by humans to now be transferred to machines. Does this mean that we are all headed into a world depicted in the Matrix or in the Terminator movies?

I think not. As these jobs get outsourced, I anticipate a blowback where society discovers that there are certain types of jobs that cannot be handled by computers at all. These are tasks where highly interrelated decisions need to be made, and where the decisions themselves have second-, third- and fourth-order implications. Also, the situations are such that these implications cannot be 'hard-coded' but keep evolving at a rate that make it necessary for the decision maker to not only follow rules but also exercise judgment. These are places where a 'human touch' is required even in a knowledge role. (I say 'even' because knowledge roles by definition should be easier to codify and outsource to computers.)

One such area that is certainly a judgment based role is risk management. Risk management is anticipating and mitigating different ways in which downside loss can impact a system. Risks can be of two types. One, there are standard 'known' risks whose frequency, pattern of occurence and downside loss impact are comparatively well-known and therefore easier to plan for and mitigate. The second are the unknown risks whose occurency and intensity cannot be predicted. Now any system needs to be set up (if it wants to survive for the long term, that is) to handle both these types of risks. But as you make the system more mechanized to handle the first type of known and predictable risks, it has lesser ability and flexibility to handle the second 'unknown' type of risk.

This is where the role of an experienced risk manager comes in. A risk manager typically has a fair amount of experience in his space. Additionally, he has the ability to maintain mental models of systems in his head which have multiple interactions and whose impacts span multiple time periods. The role of the risk manager is then to devise a system that works equally effectively against both known and unknown risks. The system needs to be such that standard breakdowns are handled without intervention. At the same time, a dashboard of metrics are created about the system which give visibility into the fundamental relationships underlying the system. And when the metrics point to the underlying fundamentals being stretched to breaking point, that's the point at which the occurence of the unexpected risks becomes imminent. The risk manager then steers the system away from being impacted by the downside implications that can result.

My role in my industry is a risk management role, and the role has given me the chance to think deeply about risk and failure modes. And it certainly seems clear to me that there will always be room for human judgment and skills in this domain.

Krish Swamy - practitioner of predictive analytics

I am a quantitative practitioner of predictive business analytics. My job gives me the opportunity to indulge in my passion: using quantitative approaches to solve business problems and understand human behaviour. My specific skills are using regression and other statistical inference techniques.